• DocumentCode
    761531
  • Title

    On the asymptotic distribution of the errors in vector quantization

  • Author

    Neuhoff, David L.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
  • Volume
    42
  • Issue
    2
  • fYear
    1996
  • fDate
    3/1/1996 12:00:00 AM
  • Firstpage
    461
  • Lastpage
    468
  • Abstract
    In a recent paper, Lee and Neuhoff (see ibid., vol.42, no.2, p446-60, 1996) found an asymptotic formula for the distribution of the length of the errors produced by a vector quantizer with many quantization points. This distribution depends on the source probability density, the quantizer point density, and the quantizer shape profile. (The latter characterizes the shapes of the quantization cells as a function of position.) The purpose of this paper is to give a rigorous derivation of this formula by identifying precise conditions under which it is shown that if a sequence of vector quantizers with a given dimension and an increasing number of points has “specific” point densities and “specific” shape profiles converging to a “model” point density and a “model” shape profile, respectively, then the distribution of the length of the quantization error, suitably normalized, converges to the aforementioned formula, with the model point density and the model shape profile substituted
  • Keywords
    error statistics; information theory; probability; vector quantisation; asymptotic error distribution; point density; quantization error length distribution; quantizer shape profile; source probability density; vector quantization; Computer science; Probability distribution; Shape; Vector quantization;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.485716
  • Filename
    485716